Dissertation Research: Disentangling drivers of community structure and composition of a tropical forest

论文研究：解开热带森林群落结构和组成的驱动因素

• 批准号: 1501175
• 负责人: David Wilcove
• 金额: $ 1.63万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1501175&HistoricalAwards=false
• 关键词: Dissertation; Research; Disentangling; drivers; community

This project seeks to disentangle and characterize drivers of plant and animal community structure and composition in one of the world's largest regenerating tropical forests. Determining why species are able to exist in a particular time and place (particularly the role of chance vs. inevitability) is simultaneously one of the most central tasks in ecology and a deeply pressing question for conservation in a rapidly changing world. Understanding these forces in regenerating tropical forest is a particularly timely given (1) the incredible biodiversity of tropical forests, (2) that the proportion of remaining forest classified as regenerating is high and ever-rising, and (3) such knowledge is a prerequisite for deploying ecological restoration as an effective tool for preserving threatened species and ecosystems.The project team will assess three ultimate drivers of community composition and structure: soil quality, landscape composition, and initial vegetative conditions. Using a network of vegetative plots, species composition of terrestrial mammal, bat, bird, and singing-insect assemblages will be assessed. Fundamental to this task is developing a set of tools that will allow for the rapid, cheap, and non-invasive assessment of these animal groups. To this end, ultrasonic and audible-frequency recorders will be deployed, and the research team is developing techniques that will allow for the semi-automated analysis of recordings using machine learning. To further assess vegetative structure and species interactions as proximate drivers of composition, arrays of synced recorders will be used to determine how key forest structural features and the distribution of some species affects the presence of others.

该项目旨在理清和描述世界上最大的再生热带森林之一的植物和动物群落结构和组成的驱动因素。 确定物种为什么能够在特定的时间和地点生存（特别是偶然性与必然性的作用）同时是生态学最核心的任务之一，也是快速变化的世界中保护的一个紧迫问题。 了解这些力量在再生热带森林是一个特别及时的考虑（1）令人难以置信的热带森林的生物多样性，（2）剩余的森林被归类为再生的比例很高，并不断上升，以及（3）这些知识是部署生态恢复作为保护受威胁物种和生态系统的有效工具的先决条件。组成和结构：土壤质量、景观组成和初始植被条件。 使用网络的植被图，陆生哺乳动物，蝙蝠，鸟类和歌唱昆虫组合的物种组成进行评估。这项任务的基础是开发一套工具，可以快速，廉价和非侵入性地评估这些动物群体。 为此，将部署超声波和音频记录器，研究团队正在开发技术，允许使用机器学习对记录进行半自动分析。 为了进一步评估植被结构和物种相互作用的组成，同步记录器阵列将被用来确定关键的森林结构特征和一些物种的分布如何影响其他物种的存在。